BOX & JENKINS METHODOLOGY: AN APLICATION IN RAW MILK DATA FROM THE STATE OF MINAS GERAIS

• Autor(a) principal: Barbosa, Eduardo Campana
• Data de Publicação: 2014
• Outros Autores: Sáfadi, Thelma, Henrique Osório Silva, Carlos, César Manuli, Rômulo
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista do Instituto de Laticínios Cândido Tostes
• Texto Completo: https://www.revistadoilct.com.br/rilct/article/view/286
• topic: forecasting; modeling; trend; seasonality; Laticínios; estatística; previsão; modelagem; tendência; sazonalidade

The Box Jenkins methodology was used to obtain a statistical model for estimate the production in liters of milk of the 6 first months of 2013 in Minas Gerais state, adjusting SARIMA (p, d, q) x (P, D, Q)s models, where d and D are the number of differences to remove the trend and seasonality of time series, p and q are the order of the autoregressive and moving average operators, P and Q are the order of theautoregressive and moving average seasonal operators and s is the seasonal periodicity.The Akaike Criterion Information (AIC) procedure was used to select the 6 mostparsimonious models and to find the best one the error indicators Mean Squared Error(EQM) and Mean Absolute Percent Error (MAPE) were analyzed, in addition to theassumptions of residues white noise. The Seasonal Autoregressive Integrated MovingAverage SARIMA (3,1,2) x (0,1,2)12 was upper, view of the principle of parsimonyand with more precise estimates. The forecast was more adjusted to the real valuesof milk production in Minas Gerais state and the model had smaller error indicators.The residues estimated were by this model white noise.